Technological advancements of recent decades have reshaped the way people socialize, work, learn, and ultimately live. The use of cyber-physical systems (CPS) specifically have helped people lead their lives with greater control and freedom. CPS domains have great societal significance, providing crucial assistance in industries ranging from security to healthcare. At the same time, machine learning (ML) algorithms are known for being substantially efficient, high performing, and have become a real standard due to greater accessibility, and now more than ever, multidisciplinary applications of ML for CPS have become a necessity to help uncover constructive solutions for real-world problems. Real-Time Applications of Machine Learning in Cyber-Physical Systems provides a relevant theoretical framework and the most recent empirical findings on various real-time applications of machine learning in cyber-physical systems. Covering topics like intrusion detection systems, predictive maintenance, and seizure prediction, this book is an essential resource for researchers, machine learning professionals, independent researchers, scholars, scientists, libraries, and academicians.
Technological advancements of recent decades have reshaped the way people socialize, work, learn, and ultimately live. The use of cyber-physical systems (CPS) specifically have helped people lead their lives with greater control and freedom. CPS domains have great societal significance, providing crucial assistance in industries ranging from security to healthcare. At the same time, machine learning (ML) algorithms are known for being substantially efficient, high performing, and have become a real standard due to greater accessibility, and now more than ever, multidisciplinary applications of ML for CPS have become a necessity to help uncover constructive solutions for real-world problems. Real-Time Applications of Machine Learning in Cyber-Physical Systems provides a relevant theoretical framework and the most recent empirical findings on various real-time applications of machine learning in cyber-physical systems. Covering topics like intrusion detection systems, predictive maintenance, and seizure prediction, this book is an essential resource for researchers, machine learning professionals, independent researchers, scholars, scientists, libraries, and academicians.
Kamal Hiran is an Innovative and Enthusiastic Academic Professional having more than 14 years of experience in Academic Administration, Teaching and Research experience in India, Europe, and Africa. I have worked on various academic positions such as Lecturer, Sr. Lecturer, Asst. Professor, Associate Professor, Head IT, Head Academics, Founder, IEEE Liberia, IEEE Ghana Technical & Professional Activity Chair, IEEE SB Coordinator. I have done the tie-up with Academic-Industry collaboration as part of my jobs such as Turnitin (Plagiarism Checker), Founder IEEE Student Branch, Ghana, and Oracle WDP. I have published and presented the research papers in the Peer-reviewed journals as well as International Conferences in India, Denmark, USA, Germany, Jordan, Ghana, and Ethiopia. Working as a Reviewer and Member in the International Program Committee in the International Journals: Journal of Medical and Biological Engineering (JMBE), Springer, Germany, IJCA USA, IGI-Global USA, and IJERT, India. Ruchi Doshi has more than 16 years of academic, research and software development experience in Asia and Africa. Currently she is working as research supervisor at the Azteca University, Mexico and Adjunct Professor at the Jyoti Vidyapeeth Women's University, Jaipur, Rajasthan, India. She worked in the BlueCrest University College, Liberia,West Africa as Registrar and Head, Examination; BlueCrest University College, Ghana, Africa; Amity University, Rajasthan, India; Trimax IT Infrastructure & Services, Udaipur, India. She worked as a Founder Chair, Women in Engineering (WIE) and Secretary Position in the IEEE Liberia Subsection. She worked with Ministry of Higher Education (MoHE) in Liberia and Ghana for the Degree approvals and accreditations processes. She is interested in the field of Machine Learning and Cloud computing framework development. She has published numerous research papers in peer-reviewed international journals and conferences. She is a Reviewer, Advisor, Ambassador and Editorial board member of various reputed International Journals and Conferences.
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